Interested in this AI/ML Engineer role at Crown Castle?
Apply Now →Skills & Technologies
About This Role
POSITION TITLE: Sr Engineer, Data & AI (P4)
For more than three decades, Crown Castle has led the way in shared communications infrastructure, delivering profitable solutions by connecting communities, businesses, and people, and enabling each to thrive with reliable access to voice and data in more places, faster than ever before. When you join Crown Castle, you become part of a dynamic team of passionate and collaborative professionals engaging in complex challenges and contributing to projects that shape the future of life and work.
ABOUT THE ROLE
The Sr. Engineer – Data & AI is a highly technical, hands-on, and execution-oriented individual who will help translate the organization’s Data, Analytics, AI, governance, and automation strategies into prioritized roadmaps, measurable business outcomes, and delivered capabilities. Working across data platforms, engineering, analytics, data science, AI, governance, and RPA, this role will combine technical execution with product ownership, portfolio planning, and coordination of strategic initiatives. The successful candidate will have the technical depth to work credibly with engineers, architects, data scientists, analysts, and business stakeholders while personally investigating problems, analyzing data, developing prototypes and lightweight solutions, and improving processes.
The role will also serve as a trusted extension of the Director of Data, Analytics & AI, taking ownership of selected priorities such as business-value measurement, executive materials, budgets and forecasts, organizational commitments, and other delegated activities. The ideal candidate is energetic, intellectually curious, highly organized, and exceptionally detail-oriented, with the communication skills, judgment, and initiative to move effectively across technical, financial, operational, and strategic topics.
WHAT YOU WILL DO
- Develop and maintain integrated roadmaps and product backlogs across data platforms, engineering, analytics, data science, AI and machine learning, Data & AI governance, and intelligent automation, translating strategy into prioritized initiatives and measurable outcomes.
- Serve as Technical Program Manager for complex Data & AI engagements and lead the organization’s Agentic AI program from business case through delivery, adoption, value realization, and ongoing operations.
- Coordinate execution across technical teams, business stakeholders, vendors, managed-service providers, and enterprise functions, managing accountability, dependencies, constraints, risks, priorities, and unresolved decisions.
- Serve as Product Manager for assigned internal Data & AI capabilities, balancing user and stakeholder needs with business value, technical feasibility, cost, risk, and strategic alignment.
- Collaborate with engineers, architects, data scientists, analysts, governance specialists, and automation professionals to evaluate designs, delivery challenges, technical risks, and architecture tradeoffs.
- Develop prototypes, analyses, data products, automations, integrations, dashboards, and utilities using code, data, APIs, AI-enabled tools, and modern engineering practices.
- Contribute hands-on to solution design, technical reviews, testing, data validation, implementation, and troubleshooting, identifying root causes and recommending solutions.
- Establish reusable intake, prioritization, planning, measurement, and reporting capabilities that reduce manual work and improve organizational effectiveness.
- Develop business cases and value hypotheses based on baselines, assumptions, expected benefits, costs, and measurable value across growth, cost optimization, productivity, risk and resilience, and foundational enablement.
- Define metrics and evaluate adoption, operational performance, and realized value to determine when capabilities require improvement, reprioritization, expansion, or retirement.
- Serve as a trusted extension of the Director, independently advancing delegated priorities with discretion, judgment, and reliable follow-through.
- Coordinate organizational planning cycles, leadership commitments, decision records, and strategic actions across capability areas.
- Support budgets, forecasts, investments, resources, vendor and contract analysis, and financial performance management.
- Recommend technology investments, sourcing strategies, and workforce needs while proactively resolving unowned organizational issues.
- Build trusted relationships across technology and the business through responsiveness, credibility, transparency, and consistent execution.
WHAT YOU WILL NEED TO SUCCEED
Education Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, Physics, Computational Science, or another highly quantitative discipline.
- Master’s or a PhD in a relevant quantitative or computational discipline preferred.
Experience Qualifications
- 7 or more years’ experience with a Masters, or 5 or more years’ experience with a Master’s or PhD, of progressively advanced experience across software engineering, data engineering, analytics engineering, data platforms, data governance, data quality, and/or related disciplines.
- A passion and enthusiasm for data, AI, analytics, governance, data management, and automation.
- High level of initiative, positive energy, curiosity, adaptability, and willingness to take ownership beyond a narrowly defined functional scope.
- Demonstrated ability to define technical strategy and lead its execution while remaining personally engaged in hands-on technical work.
- Strong technical fluency across data architecture, data engineering, analytics engineering, data science, AI and machine learning, data governance, APIs, and workflow automation, with working proficiency in technical languages, preferably Python and SQL.
- Experience managing product or capability roadmaps, backlogs, milestones, dependencies, risks, and measurable outcomes.
- Experience developing business cases, defining KPIs, quantifying expected benefits, tracking realized value, and communicating financial and operational impacts.
- Ability to translate business needs, technical designs, financial considerations, governance requirements, and executive priorities into clear direction for technical and nontechnical stakeholders.
- Exceptional written, verbal, and visual communication skills, with the credibility to influence technical professionals, business stakeholders, and senior leaders across organizational boundaries without formal authority.
- Strong analytical judgment, attention to detail, organization, accountability, and follow-through, with the ability to structure ambiguous problems and adapt rapidly to changing priorities.
- Sound judgment and discretion when handling sensitive organizational, financial, personnel, vendor, or strategic information.
Organizational Relationship
Reports to: Director of Engineering – AI, Data, Analytics, and Governance
Title(s) of direct reports (if applicable): N/A
Where You Will Work
To optimize collaboration, relationship building, and key stakeholder engagement, this role aligns to a 4:1 hybrid model which is in office in Houston, TX, Monday-Thursday with the option for remote work on Fridays.
YOUR COMPANY BENEFITS
At Crown Castle, we do our best to ensure you have access to the resources you need to live a healthy and happy life no matter where you are in life. Our benefits are built around your individual needs, covering physical, mental, and financial health and designed to enhance your quality of life.
We are proud to offer a full suite of health and wealth benefits for you and your loved ones. Below are a few of the key highlights of the many benefits we provide.
- Comprehensive healthcare plans with highly company subsidized premiums and up to $2,000 annual company contribution to your Health Savings Account (HSA base plan for employee and dependents).
- Market-leading 401(k) plan, which includes up to 10% company contributions through our 5% match and 5% profit sharing program (based on employee contributions).
- New-child leave up to 8 weeks of 100% paid leave upon birth or legal adoption of a new child. Birth mothers are eligible for up to 8 weeks of additional 100% paid medical leave.
- Tuition reimbursement up to $5,250 per year of eligible tuition and fees.
- Crown Castle scholarship program awarding up to $10,000 per recipient each year for eligible dependent children of employees and interns.
- Matching charitable contributions to qualified charitable organizations of up to $1,000 per year per teammate.
- Generous paid time-off for eligible full-time employees (minimum 18 days per year based on years of service).
- 10 company holidays plus 2 floating holiday.
- All offices provide free beverages and snacks.
Compensation
The salary range offered for this position is $148,720 - $195,195 annually. A candidate's offer is determined by various factors including but not limited to, depth of experience, role-related knowledge and skills, relevant education or training, internal alignment, and work location. Depending on the position offered, the compensation package may also include incentive compensation opportunities in the form of a discretionary annual cash bonus or commissions, and equity incentives.
Additional Information
Pursuant to the Los Angeles County and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
If you are interested in joining our team, please visit the Crown Castle careers site (https://www.crowncastle.com/careers/) to apply. We do not accept resumes from agencies, headhunters, or other third-party suppliers who have not signed a formal agreement with us. This position will remain posted until filled.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
Salary Context
This $148K-$195K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Crown Castle, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($171K) sits 19% below the category median. Disclosed range: $148K to $195K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Crown Castle AI Hiring
Crown Castle has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Houston, TX, US. Compensation range: $195K - $195K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.